metadata

language:
  - fr
license: mit
task_categories:
  - translation
tags:
  - pictograms
  - AAC
pretty_name: Propicto-polylexical

Propicto-polylexical

📝 Dataset Description

Propicto-polylexical is a dataset of aligned text and pictograms (the pictograms correspond to the identifiers associated with ARASAAC pictograms) in French. This dataset was manually created to specifically provide a resource containing texts with polylexical expressions translated into pictograms.

The dataset contains is a single file of 1,462 utterances.

⚒️ Dataset Structure

The dataset is structured as follows:

id : the unique identifier of the utterance
text : the sentence in French
pictos : the sequence of pictogram IDs from ARASAAC
tokens : the sequence of tokens, each of which is a keyword associated with an ARASAAC pictogram ID

💡 Dataset example

For the given sample :

id : 43
text : le collier du chien est trop serré il faut l'ajuster
pictos : [8476, 6987, 36480, 25708, 5380, 15523, 8476, 8516]
tokens : le collier_du_chien être trop serrer devoir le adapter

pictos is the sequence of pictogram IDs, each of them can be retrieved from here : 15523 = https://static.arasaac.org/pictograms/15523/15523_2500.png
tokens are retrieved from a specific lexicon and can be used to train translation models.

💻 Uses

Propicto-polylexical is intended to be used to train Text-to-Pictograms translation models. This dataset can also be used to fine-tune large language models to perform translation into pictograms.

⚙️ Dataset Creation

The dataset is created by applying a specific formalism that converts french transcriptions into a corresponding sequence of pictograms.
The formalism includes a set of grammatical rules to handle specific phenomenon (negation, name entities, pronominal form, plural, ...) to the French language, as well as a dictionary which associates each ARASAAC ID pictogram with a set of keywords (tokens).
This formalism was presented at LREC.

⁉️ Limitations

The translation can be partially incorrect, due to incorrect or missing words translated into pictograms.

💡 Information

Curated by: Cécile MACAIRE
Funded by : PROPICTO ANR-20-CE93-0005
Language(s) (NLP): French
License: CC-BY-NC-SA-4.0

📌 Citation

@inproceedings{macaire-etal-2024-multimodal,
    title = "A Multimodal {F}rench Corpus of Aligned Speech, Text, and Pictogram Sequences for Speech-to-Pictogram Machine Translation",
    author = "Macaire, C{\'e}cile  and
      Dion, Chlo{\'e}  and
      Arrigo, Jordan  and
      Lemaire, Claire  and
      Esperan{\c{c}}a-Rodier, Emmanuelle  and
      Lecouteux, Benjamin  and
      Schwab, Didier",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    year = "2024",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.76",
    pages = "839--849",
}

👩‍🏫 Dataset Card Authors

Cécile MACAIRE, Chloé DION, Emmanuelle ESPÉRANÇA-RODIER, Benjamin LECOUTEUX, Didier SCHWAB